Speci cation Search and Stability Analysis

Most speci cation search processes select models based on some goodness of t statistic (i.e. R or related F ). The e ects of the sequential search on the statistical tests should be taken into account when looking for the maximum goodness of t. To avoid misspeci ed models it is useful to study the selected models based on the full sample, and along the sample. This paper presents a conditional sequential procedure to be used in the speci cation search process of linear regression models, as a way to minimize data snooping or data mining. It is a combined test, rst it considers the search for the \best" set of regressors, and conditional on this set, it studies their signi cance along the sample. The characteristics of the conditional test are presented. Its usefulness is considered with one application.